FAIR Enough? Enhancing the Usage of Enterprise Data with Data Catalogs

Labadie, Clément; Legner, Christine; Eurich, Markus; Fadler, Martin

doi:10.1109/cbi49978.2020.00029

Cited by 25 publications

(15 citation statements)

References 12 publications

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“…According to Sheridan et al [3], a data catalogue "is a curated collection of metadata records that describe and point to data products of interest." To achieve these purposes, they should be supported by an IS-specific class type that meets FAIR principles by promoting documentation [9] and metadata management [10]. This paper focuses on catalogues storing metadata of research datasets, allowing for their discovery, access, and understanding.…”

Section: Metadata and The Data Catalogue Domainmentioning

confidence: 99%

Ontology-Driven Multi-Level Conceptual Modeling for Dataset and Distributions Descriptions

Borges,

Prata,

Campos

2023

Frontiers in Artificial Intelligence and Applications

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This paper presents an improvement proposal for an ontology-driven multi-level conceptual model for the data catalogue domain. Data catalogues gather metadata that describe resources in different and heterogeneous digital platforms (repositories). They are supported by Information Systems (IS) that use these descriptors to provide visibility and support resources exploration and analysis. Domain ontologies are essential to promote quality ISs, as they are developed to reflect the intended reality. The proposed conceptual model is well-founded on the Unified Foundational Ontology and the Multi-Level Theory, based on the widely used DCAT vocabulary, a standardized metadata schema for describing datasets and data services. The resulting model addresses ambiguities and contemplates high-level types contributing to the conformance of domain concepts and relationships. In addition, they provide knowledge about the different types of resource descriptors and relationships contained in a specific catalogue, favoring its management. The paper enhances the previous model by extending it to handle descriptors representing a dataset according to the data equivalence across multiple distributions. We also demonstrate the model by describing a dataset with no data equivalence in its distributions, taken from a real-world scenario, thus providing a structured representation to manage metadata sets in the data catalogue domain.

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Section: Metadata and The Data Catalogue Domainmentioning

confidence: 99%

Ontology-Driven Multi-Level Conceptual Modeling for Dataset and Distributions Descriptions

Borges,

Prata,

Campos

2023

Frontiers in Artificial Intelligence and Applications

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“…Interactive multidimensional analysis, with rich report components, supports real-time scheduled tasks and achieves terabyte-level data with second-level response. The current ″data resource catalog″ is the result of the evolution of different concepts established by companies for data documents and data provision since the early 1960s when data processing began . To this day, data documents are usually associated with metadata.…”

Section: Introductionmentioning

confidence: 99%

“…The current ″data resource catalog″ is the result of the evolution of different concepts established by companies for data documents and data provision since the early 1960s when data processing began. 12 To this day, data documents are usually associated with metadata. Metadata is often defined as ″data about data″ and ″aimed at facilitating access, management, and sharing of large amounts of structured and unstructured data″.…”

Section: Introductionmentioning

confidence: 99%

Construction and Application of a Big Data System for Regional Lakes in Coalbed Methane Development

Wang¹,

Adenutsi

Wang³

et al. 2023

ACS Omega

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With the rapid development and widespread application of big data and artificial intelligence, the upgrading of digital and intelligent industries has been rapidly popularized in the oil and gas industry. First, based on the theory of ″regional data lake″, the digital nature of the CBM governance system is analyzed, and the optimization model of CBM governance for different data types is established. Second, considering the geological characteristics and development mode of the CBM reservoir, the regional data lake expansion model is established. Third, a theoretical model of coupling ″on-site data, laboratory data, management data, and data management system″ has been established. The research shows the following: (a) The CBM governance system based on the regional data lake can be divided into four parts: basic support, data life cycle, core governance areas, and governance strategy support. (b) The coupling of the coalbed methane governance model with the BP neural network model in this article has good application results. (c) The computational efficiency of this model has been improved by 12%, which has broad application prospects.

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“…15 periphery, empowering cooperation, expanding new energy (sources), and digital management." 16 Based on the above strategic objectives, CBM has extensively studied the integration of geology and gas engineering technologies and their application prospects in the field of geological and gas reservoir engineering. 17−21 Baker Hughes' integrated geology and engineering research platform integrates three major software packages�geological modeling, geomechanical modeling, and fracturing software�into one integrated geological engineering research platform.…”

Section: Introductionmentioning

confidence: 99%

“…This is the only way to achieve gas storage and production increase and effective economic development . Therefore, CBM Company has firmly established the concept of “deep overburden, high quality and dense, shallow and deep plowing, shale research, developing new fields, breaking through the periphery, empowering cooperation, expanding new energy (sources), and digital management.” Based on the above strategic objectives, CBM has extensively studied the integration of geology and gas engineering technologies and their application prospects in the field of geological and gas reservoir engineering. − Baker Hughes’ integrated geology and engineering research platform integrates three major software packagesgeological modeling, geomechanical modeling, and fracturing softwareinto one integrated geological engineering research platform. − It realizes from seismic data interpretation, structural modeling, three-dimensional (3D) geological modeling, and 3D geomechanical modeling. − It is used for drilling optimization design, engineering fracturing application, and reservoir numerical simulation. Based on (open group open subsurface data universe) OSDU’s upstream data management platform, Schlumberger’s DELFI Geological Integrated Research Environment integrates a range of native cloud applications into Petrel’s specialized software core. − It enables integrated studies of exploration, geology, modeling, numerical simulation, well completion, and production.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Decision-Making System for Integrated Geological and Engineering of Deep Coalbed Methane Development

Wang,

Huang

et al. 2023

Energy Fuels

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Coalbed methane (CBM) exploration and development is becoming increasingly complex, and the deterioration of resource quality is intensifying. In this paper, first, based on the research results of data regional lake and fine description of gas reservoirs, artificial intelligence technology was applied to deep mining and analysis of comprehensive data of CBM reservoirs. Second, an innovative integrated CBM geology engineering intelligent decision-making system based on big data analysis algorithms was developed. Third, the fast single-well production prediction and master controlling factor analysis driven by big data is achieved. Fourth, comprehensive sweet spot analysis was conducted on CBM reservoirs by combining geological and engineering factors. The fracturing parameters based on the analysis of the main control factors of production after fracturing of CBM wells were optimized. The system is promoted and applied in Daning block on the east edge of the Ordos Basin. Results show that (a) the system has significantly improved the efficiency of gas reservoir research and the effectiveness of engineering decisions, and (b) it provides a powerful new method and system support for fully understanding the resource potential of gas reservoirs and comprehensively promoting the deep application of intelligence in scientific research and production.

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FAIR Enough? Enhancing the Usage of Enterprise Data with Data Catalogs

Cited by 25 publications

References 12 publications

Ontology-Driven Multi-Level Conceptual Modeling for Dataset and Distributions Descriptions

Ontology-Driven Multi-Level Conceptual Modeling for Dataset and Distributions Descriptions

Construction and Application of a Big Data System for Regional Lakes in Coalbed Methane Development

Intelligent Decision-Making System for Integrated Geological and Engineering of Deep Coalbed Methane Development

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